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adk-agent-builder

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Actualizado7 de julio de 2026 a las 21:13

Central hub for building, testing, and iterating on ADK agents. Trigger this skill when the user wants to create a new agent, configure modes (task, single-turn), or build graph-based workflows.

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Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.

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OMIXEC

OMIXEC/Google-ADK-Skills

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SKILL.md

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name	adk-agent-builder
description	Central hub for building, testing, and iterating on ADK agents. Trigger this skill when the user wants to create a new agent, configure modes (task, single-turn), or build graph-based workflows.

ADK Agent Builder

This file serves as a directory of specialized reference guides for developing agents with ADK. To avoid context pollution, read only the relevant reference file based on your current task.

Before choosing import paths, package versions, graph APIs, or examples, read ../../docs/python-adk-2.md.

Core Concepts Directory

Refer to these files for foundational knowledge:

Getting Started & Basic Agents: getting-started.md
- Environment setup, API key configuration, and minimal agent definitions.
Tool Catalog: tool-catalog.md
- How to bind function tools, MCP tools, OpenAPI specs, and Google API tools.
Agent Modes (Task / Single-Turn): task-mode.md
- Multi-turn structured delegation and autonomous single-turn execution patterns.

Workflow & Graph Orchestration

Refer to these files when building complex graphs:

Function Nodes: function-nodes.md
- How to use functions as nodes, type resolution, and generators.
Routing & Conditions: routing-and-conditions.md
- Edge patterns, dict-based routing, self-loops, and conditional execution.
LLM Agent Nodes: llm-agent-nodes.md
- How to use LLM agents as workflow nodes, task wrappers, and handling output schemas.

Advanced Orchestration Patterns

Parallel Processing & Fan-Out: parallel-and-fanout.md
- ParallelWorker for list splitting and concurrent processing, fan-out/join patterns.
Human-in-the-Loop: human-in-the-loop.md
- Pausing execution for user input, resumable workflows, and AuthConfig on nodes.
Dynamic Nodes: dynamic-nodes.md
- Scheduling nodes at runtime dynamically via ctx.run_node().

Infrastructure & Utilities

State & Events: state-and-events.md
- Using context API, sharing global state, and yield event structures.
Multi-Agent Systems: multi-agent.md
- Hierarchical execution (e.g., SequentialAgent, LoopAgent, ParallelAgent).
Testing Strategies: testing.md
- Automated queries with adk run, unit tests, and integration testing with sample agents.

Standards & Guidelines

Best Practices: best-practices.md
- Critical rules (Pydantic schemas, content events, state-based data flow).

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ADK Agent Builder

This file serves as a directory of specialized reference guides for developing agents with ADK. To avoid context pollution, read only the relevant reference file based on your current task.

Before choosing import paths, package versions, graph APIs, or examples, read ../../docs/python-adk-2.md.

Core Concepts Directory

Refer to these files for foundational knowledge:

Getting Started & Basic Agents: getting-started.md

Environment setup, API key configuration, and minimal agent definitions.

Tool Catalog: tool-catalog.md

How to bind function tools, MCP tools, OpenAPI specs, and Google API tools.

Agent Modes (Task / Single-Turn): task-mode.md

Multi-turn structured delegation and autonomous single-turn execution patterns.

Workflow & Graph Orchestration

Refer to these files when building complex graphs:

Function Nodes: function-nodes.md

How to use functions as nodes, type resolution, and generators.

Routing & Conditions: routing-and-conditions.md

Edge patterns, dict-based routing, self-loops, and conditional execution.

LLM Agent Nodes: llm-agent-nodes.md

How to use LLM agents as workflow nodes, task wrappers, and handling output schemas.

Advanced Orchestration Patterns

Parallel Processing & Fan-Out: parallel-and-fanout.md

ParallelWorker for list splitting and concurrent processing, fan-out/join patterns.

Human-in-the-Loop: human-in-the-loop.md

Pausing execution for user input, resumable workflows, and AuthConfig on nodes.

Dynamic Nodes: dynamic-nodes.md

Scheduling nodes at runtime dynamically via ctx.run_node().

Infrastructure & Utilities

State & Events: state-and-events.md

Using context API, sharing global state, and yield event structures.

Multi-Agent Systems: multi-agent.md

Hierarchical execution (e.g., SequentialAgent, LoopAgent, ParallelAgent).

Testing Strategies: testing.md

Automated queries with adk run, unit tests, and integration testing with sample agents.

Standards & Guidelines

Best Practices: best-practices.md

Critical rules (Pydantic schemas, content events, state-based data flow).